Context-awareness’ could be one of the most desired fundamental abilities that a robot should have when sharing a workspace with humans co-workers. Arguably, a robot with appropriate context-awareness could lead to a better human robot interaction. In this paper, we address the problem of combining context- awareness with robotic path planning. Our approach is based on affordance-map, which involves mapping latent human actions in a given environment by looking at geometric features of the environment. This enables us to learn human context in an given environment without observing real human behaviours which them- selves are a non-trivial task to detect. Once learned, affordance-map allows us to assign anaffordance cost value for each grid location of the map. These cost maps are later used to develop a context-aware global path planning strategy by using the well known A* algorithm. The proposed method was tested in a real office environment and proved our algorithm is capable of moving a robot in a path that minimises the distractions to human co-workers.

en_US

dc.publisher

Australian Robotics and Automation Association Inc

en_US

dc.relation.ispartof

Proceedings of the Australasian Conference on Robotics and Automation 2014

en_US

dc.relation.ispartof

Australasian Conference on Robotics and Automation 2014

en_US

dc.title

Affordance-Map : A Map for Context-Aware Path Planning.

en_US

dc.type

Conference Proceeding

utslib.description.version

Published

en_US

utslib.location

Australia

en_US

utslib.location.activity

Melbourne

en_US

utslib.for

091303 Autonomous Vehicles

en_US

dc.location.activity

Melbourne

dc.location.activity

Melbourne

dc.location.activity

Melbourne

dc.location.activity

Melbourne

pubs.embargo.period

Not known

en_US

pubs.organisational-group

/University of Technology Sydney

pubs.organisational-group

/University of Technology Sydney/Faculty of Engineering and Information Technology

pubs.organisational-group

/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Elec, Mech and Mechatronic Systems

Context-awareness’ could be one of the most desired fundamental abilities that a robot should have when sharing a workspace with humans co-workers. Arguably, a robot with appropriate context-awareness could lead to a better human robot interaction. In this paper, we address the problem of combining context- awareness with robotic path planning. Our approach is based on affordance-map, which involves mapping latent human actions in a given environment by looking at geometric features of the environment. This enables us to learn human context in an given environment without observing real human behaviours which them- selves are a non-trivial task to detect. Once learned, affordance-map allows us to assign anaffordance cost value for each grid location of the map. These cost maps are later used to develop a context-aware global path planning strategy by using the well known A* algorithm. The proposed method was tested in a real office environment and proved our algorithm is capable of moving a robot in a path that minimises the distractions to human co-workers.

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